AI and Machine Learning Trends in IT

Machine learning and artificial intelligence have become popular keywords while organizational across all industries seek to find ways of utilizing these technologies to optimise work, gain deeper understanding and enhance the delivery of services to customers. IT is not an exception – AI and ML can be considered the main agents of some of the most promising trends in the industry. Below are some of the trends in application of AI and machine learning in IT that defines tomorrow.

Automation Using AI and ML

Some of the IT activities that are currently being done manually and with high repetitiveness are now implemented with help of AI and ML algorithms. This includes things such as Predictive Maintenance, Automated Incident Remediation and Password Reset etc. Automating the process will allow the IT teams to release some of their human resource to accomplish the more important strategic projects. According to Gartner it is estimated that by 2025 40 percent of large organizations would employ AI-infused automation in IT operations teams.

The ability to allow computers to understand, analyze and manipulate human language commonly referred to as natural language understanding (NLU) and the process of recognizing speech and converting it to text, usually known as speech recognition or speech-to-text are together collectively referred to as natural language processing (NLP).

NLP is the one of the most rapidly growing part of the AI industry today, and it is changing the ways people communicate with machines. It is imperative to note that tier-1 service desk requests are being adopted by IT support teams which are using chatbots and virtual agents driven by NLP. This makes work more efficient and customers content with option of self-service anytime of the day. NLP also creates new PI for managing IT infrastructure and application via voice control.

AIOps

The combination of AI and ML known as AIOps with reference to the data analysis, monitoring, automation and other relevant activities related to IT. It helps to achieve a smarter IT Ops with the help of pattern and anomaly recognition, resource demand prediction, and configuration optimization and anything in between. IDC has it that greater than 50% of large enterprise will leverage AIOps to improve IT resilience and reliability by year 2025. This is where AIOps platform can be sourced from third-party vendors than include Moogsoft, BigPanda, and FixStream.

Computer Vision

Computer vision is a field that employs ML to interpret images, videos, and simulations as well as any other type of imagery. In IT, computer vision can perform visual inspection and quality control, provide security aid in facial recognition, and video analysis. Second, it also facilitates the prediction of maintenance because it can detect defects or abnormal infrastructures. Computer vision and its related market is anticipated to reach $23.76 billion by 2030.

Augmented Analytics

This means that augmented analytics uses ML / AI techniques to intel and insights extraction in support of data analysis. In IT, the areas where augmented analytics has significant applications are infrastructure management, application Rationalization, BI reporting, and predictive applications. Provided a quicker and more complex data modeling is feasible when the human bias factor is eliminated. A recent report by Gartner shows that by 2025, over 80 percent of analyses will be done using the power of augmented analytics.

The maturing of strategic digital transformation is destined to see AI and machine learning integrated into IT environments, processes, and solutions at an accelerating rate. Business IT managers should pay close attention to these tactics and seek to leverage AI automation and intelligence to important system and processes. The results of this study show that AI and ML offer significant potential benefits in terms of business differentiation and operating models. These trends highlighted here only form a small fraction of what will become possible as these exponential technologies continue to improve at unprecedented rates.